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Background <p>There is limited evidence regarding the association between weather and <i>Plasmodium vivax</i> (<i>Pv</i>), particulary in Latin America where <i>Pv</i> is the predominant malaria species and key challenge for countries to achieve malaria elimination.</p> Methods <p>We analyzed the association between weather and <i>Pv</i> malaria incidence from 2017 to 2024 in 136 communities in the Peruvian Amazon. Monthly community-level incidence was calculated using <i>Pv</i> case data from Notiweb, the national epidemiological surveillance system, and population census data. Predictors included weekly minimum and maximum temperature and total weekly precipitation and were calculated using hourly weather from the climate dataset ERA5. Non-linear distributed lag models were fit using a lookback period of 2–16&#xa0;weeks. Temperature models were adjusted for total precipitation; precipitation models were adjusted for maximum temperature. Sub-group analyses were conducted by community type (adjacent to river versus highway) and El Niño Southern Oscillation (ENSO) period.</p> Results <p>Minimum temperature at the 90th percentile (23.7°C) was associated with 10% (95% CI 5–14%) higher malaria incidence compared to the 5th percentile (20.5°C) at a 7-week lag. Maximum temperature at the 90th percentile (33.7°C) was associated with 10% (95% CI 8–13%) higher malaria incidence compared to the 5th percentile (29.6°C) at a 9-week lag. Total weekly precipitation at the 90th percentile (1000&#xa0;mm) was associated with 29% (95% CI 24–33%) higher malaria incidence compared to weeks with the 5th percentile (57&#xa0;mm) at an 11-week lag. Incidence was higher and associations were stronger in communities adjacent to rivers versus highways. Malaria incidence was lower during El Niño periods, and there was evidence of interaction on the multiplicative scale for the association between incidence, all weather predictors, and ENSO period.</p> Conclusions <p><i>Pv</i> malaria incidence was positively associated with higher temperatures and precipitation in an elimination setting in Peru, particularly in riverine communities during non-El Niño years, with longer lag periods than previously reported for such associations. These findings can inform malaria elimination interventions to combat the long-lasting effects of weather on <i>Pv</i> transmission.</p>

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Associations between weather and Plasmodium vivax malaria in an Amazonian elimination setting: a distributed lag analysis from 2017 to 2024

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Gabriella Barratt Heitmann,
  • Xue Wu,
  • Anna T. Nguyen,
  • Astrid Altamirano-Quiroz,
  • Sydney R. Fine,
  • Bryan Fernandez-Camacho,
  • Antony Barja,
  • Renato Cava,
  • Verónica Soto-Calle,
  • Hugo Rodriguez,
  • Gabriel Carrasco-Escobar,
  • Adam Bennett,
  • Alejandro Llanos-Cuentas,
  • Erin A. Mordecai,
  • Michelle S. Hsiang,
  • Jade Benjamin-Chung

摘要

Background

There is limited evidence regarding the association between weather and Plasmodium vivax (Pv), particulary in Latin America where Pv is the predominant malaria species and key challenge for countries to achieve malaria elimination.

Methods

We analyzed the association between weather and Pv malaria incidence from 2017 to 2024 in 136 communities in the Peruvian Amazon. Monthly community-level incidence was calculated using Pv case data from Notiweb, the national epidemiological surveillance system, and population census data. Predictors included weekly minimum and maximum temperature and total weekly precipitation and were calculated using hourly weather from the climate dataset ERA5. Non-linear distributed lag models were fit using a lookback period of 2–16 weeks. Temperature models were adjusted for total precipitation; precipitation models were adjusted for maximum temperature. Sub-group analyses were conducted by community type (adjacent to river versus highway) and El Niño Southern Oscillation (ENSO) period.

Results

Minimum temperature at the 90th percentile (23.7°C) was associated with 10% (95% CI 5–14%) higher malaria incidence compared to the 5th percentile (20.5°C) at a 7-week lag. Maximum temperature at the 90th percentile (33.7°C) was associated with 10% (95% CI 8–13%) higher malaria incidence compared to the 5th percentile (29.6°C) at a 9-week lag. Total weekly precipitation at the 90th percentile (1000 mm) was associated with 29% (95% CI 24–33%) higher malaria incidence compared to weeks with the 5th percentile (57 mm) at an 11-week lag. Incidence was higher and associations were stronger in communities adjacent to rivers versus highways. Malaria incidence was lower during El Niño periods, and there was evidence of interaction on the multiplicative scale for the association between incidence, all weather predictors, and ENSO period.

Conclusions

Pv malaria incidence was positively associated with higher temperatures and precipitation in an elimination setting in Peru, particularly in riverine communities during non-El Niño years, with longer lag periods than previously reported for such associations. These findings can inform malaria elimination interventions to combat the long-lasting effects of weather on Pv transmission.